Volume 30 Issue 2
Apr.  2024
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JIANG Chenyi, PAN Jiawei, ZHANG Lijun, et al., 2024. Application of UAV SfM technology in active tectonic research: A case study of the Longmu Co Fault, Northwestern Qinghai-Tibet Plateau. Journal of Geomechanics, 30 (2): 332-347. DOI: 10.12090/j.issn.1006-6616.2023192
Citation: JIANG Chenyi, PAN Jiawei, ZHANG Lijun, et al., 2024. Application of UAV SfM technology in active tectonic research: A case study of the Longmu Co Fault, Northwestern Qinghai-Tibet Plateau. Journal of Geomechanics, 30 (2): 332-347. DOI: 10.12090/j.issn.1006-6616.2023192

Application of UAV SfM technology in active tectonic research: A case study of the Longmu Co Fault, Northwestern Qinghai-Tibet Plateau

doi: 10.12090/j.issn.1006-6616.2023192
Funds:

the Geological Survey Project of the China Geological Survey DD20221630

the National Natural Science Foundation of China 42372274

the National Science and Technology Basic Resources Investigation Program of China 2021FY100101

More Information
  • Received: 2023-12-01
  • Revised: 2024-03-18
  • Accepted: 2024-03-25
  • Available Online: 2024-04-09
  • Published: 2024-04-28
  •   Objective  In recent years, UAV (Unmanned Aerial Vehicle) SfM (Structure from Motion) technology has been widely applied as an emerging high-precision 3D topographic data acquisition technique in active tectonics research. However, existing domestic research primarily focuses on UAV platforms without RTK/PPK modules. Over the past two years, RTK and PPK technologies have gradually been introduced to UAV platforms, resulting in changes to field data collection and in-office data processing workflows compared to traditional UAV platforms without RTK/PPK modules. The differences in topographic data quality obtained through SfM processing of aerial photographs from UAV platforms equipped and not equipped with RTK/PPK modules under the same scenes and collection conditions still require investigation.  Methods  To address these questions and establish a streamlined data collection and processing workflow for different UAV platforms, a site where alluvial terraces are offset by the sinistral Longmu Co fault, northwestern Qinghai-Tibet Plateau, was surveyed using the DJI M300 RTK UAV (equipped with the Zenmuse L1 LiDAR and a 20-megapixel visible light camera) and the DJI Phantom 4 Pro UAV (equipped with a 20-megapixel visible light camera). Through processing the raw data with SfM technology, high-resolution and high-precision DEM and DOM data were obtained for the study area. Additionally, 16 ground control points (checkpoints) were uniformly distributed in the research area, and their coordinates were measured using the Trimble R8 GNSS receiver in RTK mode to compare and validate the differences in data quality obtained by the two platforms.  Results  The data comparison showed that the visible light camera and LiDAR module carried by the M300 RTK demonstrated high accuracy, with root mean square errors (RMSEs) in the centimeter to decimeter range compared to the RTK-measured ground checkpoints. Compared to SfM data collected at the same time (RMSEX=0.176, RMSEY=0.099, RMSEZ=0.180, RMSEH=0.201, RMSE3D=0.270, unit: m), the Zenmuse L1 LiDAR data exhibited slightly higher accuracy (RMSEX=0.112, RMSEY=0.076, RMSEZ=0.111, RMSEH=0.135, RMSE3D=0.174, unit: m). The uncorrected SfM data from the Phantom 4 Pro had horizontal errors of approximately 1 meter (RMSEX=1.112, RMSEY=1.295, unit: m) and a vertical error of over 200 meters (RMSEZ=249.286, unit: m). After ground control point correction, the accuracy of the Phantom 4 Pro SfM data significantly improved, with RMSE of 0.046 m, 0.058 m, and 0.527 m in the X, Y, and Z directions, respectively. Further analysis of a topographic profile nearly perpendicular to the steep slopes of various terrace risers within the surveyed area revealed that, despite significant elevation discrepancies in the uncorrected Phantom 4 Pro SfM data, it still accurately reflected the relative topographic relief. Subtracting the profile elevation values from their corresponding RMSE, the profile shape closely matched the rest of the data. Based on the acquired DEM data, the displacement of the terrace at this location was measured using LaDiCaoz software, revealing a left-lateral strike-slip displacement of 122.5±5 m and a vertical displacement of 0.8±0.2 m.  Conclusion  The study results indicate that: (1) UAV SfM method and LiDAR technology have significantly improved the resolution of DOM and DEM, enabling more detailed interpretation and analysis of active faults and related structural landforms; (2) RTK SfM technology overcomes the limitations of using ground control points, providing a higher-precision and more efficient solution for micro-landform measurements in the field of active tectonics research; (3) when absolute three-dimensional coordinates in the study area are not crucial, and only relative terrain variations are required, UAVs without RTK modules can still meet the basic requirements for geomorphic fault displacement measurements in the absence of ground control point constraints; (4) combining UAV SfM technology with traditional fault geomorphology analysis and Quaternary dating techniques in high-precision quantitative active tectonics research can offer robust technical support for analyzing fault activity patterns, seismic hazard, landform evolution, and the occurrence patterns of geological disasters.  Significance  Through the aforementioned work, workflows for data collection, data processing, and geomorphic fault displacement measurement using SfM methods in active tectonics research were established for both UAV platforms equipped and not equipped with RTK/PPK modules. The fieldwork considerations and data accuracy of UAV SfM methods were analyzed, providing a reference for selecting UAV platforms and rapidly collecting and processing data for similar studies in the future.

     

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  • AGÜERA-VEGA F, CARVAJAL-RAMÍREZ F, MARTÍNEZ-CARRICONDO P, 2017. Accuracy of digital surface models and orthophotos derived from unmanned aerial vehicle photogrammetry[J]. Journal of Surveying Engineering, 143(2): 04016025. doi: 10.1061/(ASCE)SU.1943-5428.0000206
    ARMIJO R, TAPPONNIER P, HAN T L, 1989. Late Cenozoic right-lateral strike-slip faulting in southern Tibet[J]. Journal of Geophysical Research: Solid Earth, 94(B3): 2787-2838. doi: 10.1029/JB094iB03p02787
    BEMIS S P, MICKLETHWAITE S, TURNER D, et al., 2014. Ground-based and UAV-based photogrammetry: a multi-scale, high-resolution mapping tool for structural geology and paleoseismology[J]. Journal of Structural Geology, 69: 163-178. doi: 10.1016/j.jsg.2014.10.007
    BI H Y, ZHENG W J, REN Z K, et al., 2017. Using an unmanned aerial vehicle for topography mapping of the fault zone based on structure from motion photogrammetry[J]. International Journal of Remote Sensing, 38(8-10): 2495-2510. doi: 10.1080/01431161.2016.1249308
    BI H Y, ZHENG W J, ZENG J Y, et al., 2017. Application of SfM photogrammetry method to the quantitative study of active tectonics[J]. Seismology and Geology, 39(4): 656-674. (in Chinese with English abstract) doi: 10.3969/j.issn.0253-4967.2017.04.003
    CAO P J, CHENG S Y, LIN H X, et al., 2021. DEM in quantitative analysis of structural geomorphology: application and prospect[J]. Journal of Geomechanics, 27(6): 949-962. (in Chinese with English abstract)
    CHEN X Y, SHI Y Z, YANG Y, et al., 2023. Accuracy evaluation of structure from motion (SfM) photogrammetry on the measurement of typical gullies in the Loess Plateau[J]. Journal of Shaanxi Normal University (Natural Science Edition), 51(6): 25-36. (in Chinese with English abstract)
    CHEVALIER M L, PAN J W, LI H B, et al., 2017. First tectonic-geomorphology study along the Longmu-Gozha Co fault system, western Tibet[J]. Gondwana Research, 41: 411-424. doi: 10.1016/j.gr.2015.03.008
    DENG Q D, CHEN L C, RAN Y K, 2004. Quantitative studies and applications of active tectonics[J]. Earth Science Frontiers, 11(4): 383-392. (in Chinese with English abstract)
    FONSTAD M A, DIETRICH J T, COURVILLE B C, et al., 2013. Topographic structure from motion: a new development in photogrammetric measurement[J]. Earth Surface Processes and Landforms, 38(4): 421-430. doi: 10.1002/esp.3366
    GUO Q H, HU T Y, LIU J, et al., 2021. Advances in light weight unmanned aerial vehicle remote sensing and major industrial applications[J]. Progress in Geography, 40(9): 1550-1569. (in Chinese with English abstract) doi: 10.18306/dlkxjz.2021.09.010
    HAN S, WU Z H, WANG S F, et al., 2023. Surface deformation and tectonic implication of the late Quaternary Bue Co strike-slip fault system, mid-western Qiangtang block [J/OL]. Journal of Geomechanics, DOI: 10.12090/j.issn.1006-6616.2023086 (in Chinese with English abstract).
    HARWIN S, LUCIEER A, 2012. Assessing the accuracy of georeferenced point clouds produced via multi-view stereopsis from unmanned aerial vehicle (UAV) imagery[J]. Remote Sensing, 4(6): 1573-1599. doi: 10.3390/rs4061573
    JAMES M R, ROBSON S, 2012. Straightforward reconstruction of 3D surfaces and topography with a camera: accuracy and geoscience application[J]. Journal of Geophysical Research: Earth Surface, 117(F3): F03017.
    JIMÉNEZ-JIMÉNEZ S I, OJEDA-BUSTAMANTE W, DE JESÚSMARCIAL-PABLO M, et al., 2021. Digital terrain models generated with low-cost UAV photogrammetry: methodology and accuracy[J]. ISPRS International Journal of Geo-Information, 10(5): 285. doi: 10.3390/ijgi10050285
    JOHNSON K, NISSEN E, SARIPALLI S, et al., 2014. Rapid mapping of ultrafine fault zone topography with structure from motion[J]. Geosphere, 10(5): 969-986. doi: 10.1130/GES01017.1
    KANG W J, XU X W, YU G H, et al., 2020. Comparison study of two kinds of codes to measure fault-offsets based on matlab: a case study on eastern Altyn Tagh Fault[J]. Seismology and Geology, 42(3): 732-747. (in Chinese with English abstract) doi: 10.3969/j.issn.0253-4967.2020.03.013
    KOZMUS TRAJKOVSKI K, GRIGILLO D, PETROVIČ D, 2020. Optimization of UAV flight missions in steep terrain[J]. Remote Sensing, 12(8): 1293. doi: 10.3390/rs12081293
    LI H, CHEVALIER M L, TAPPONNIER P, et al., 2021. Block tectonics across western Tibet and multi-millennial recurrence of great earthquakes on the Karakax Fault[J]. Journal of Geophysical Research: Solid Earth, 126(12): e2021JB022033. doi: 10.1029/2021JB022033
    LI H Q, YUAN D Y, SU Q, et al., 2023. Geomorphic features of the Menyuan basin in the Qilian Mountains and its tectonic significance[J]. Journal of Geomechanics, 29(6): 824-841.
    LIAO C, LIANG M J, ZHOU W Y, et al., 2024. Quantitative parameter extraction of seismic surface rupture based on SfM method and LaDiCaoz: take the typical surface rupture in Luho Zhajiao Village Area as an example[J]. Journal of Geodesy and Geodynamics, 44(2): 183-188. (in Chinese with English abstract)
    MA X X, WU Z H, LI J C, 2016. LiDAR technology and its application and prospect in geological environment[J]. Journal of Geomechanics, 22(1): 93-103. (in Chinese with English abstract)
    MICHELETTI N, CHANDLER J H, LANE S N, 2015. Investigating the geomorphological potential of freely available and accessible structure-from-motion photogrammetry using a smartphone[J]. Earth Surface Processes and Landforms, 40(4): 473-486. doi: 10.1002/esp.3648
    MOREELS P, PERONA P, 2007. Evaluation of features detectors and descriptors based on 3D objects[J]. International Journal of Computer Vision, 73(3): 263-284. doi: 10.1007/s11263-006-9967-1
    NESBIT P R, HUGENHOLTZ C H, 2019. Enhancing UAV-SFM 3D model accuracy in high-relief landscapes by incorporating oblique images[J]. Remote Sensing, 11(3): 239. doi: 10.3390/rs11030239
    OSKIN M E, LE K, STRANE M D, 2007. Quantifying fault-zone activity in arid environments with high-resolution topography[J]. Geophysical Research Letters, 34(23): L23S05.
    PERRIN C, MANIGHETTI I, AMPUERO J P, et al., 2016. Location of largest earthquake slip and fast rupture controlled by along‐strike change in fault structural maturity due to fault growth[J]. Journal of Geophysical Research: Solid Earth, 121(5): 3666-3685. doi: 10.1002/2015JB012671
    RATERMAN N S, COWGILL E, LIN D, 2007. Variable structural style along the Karakoram fault explained using triple-junction analysis of intersecting faults[J]. Geosphere, 3(2): 71-85. doi: 10.1130/GES00067.1
    REN Z K, CHEN T, ZHANG H P, et al., 2014. LiDAR survey in active tectonics studies: an introduction and overview[J]. Acta Geologica Sinica, 88(6): 1196-1207. (in Chinese with English abstract)
    ROSAS M A, CLAPUYT F, VIVEEN W, et al., 2023. Quantifying geomorphic change in Andean river valleys using UAV-PPK-SfM techniques: an example from the western Peruvian Andes[J]. Geomorphology, 435: 108766. doi: 10.1016/j.geomorph.2023.108766
    ROSNELL T, HONKAVAARA E, 2012. Point cloud generation from aerial image data acquired by a quadrocopter type micro unmanned aerial vehicle and a digital still camera[J]. Sensors, 12(1): 453-480. doi: 10.3390/s120100453
    SANZ-ABLANEDO E, CHANDLER J H, RODRÍGUEZ-PÉREZ J R, et al., 2018. Accuracy of Unmanned Aerial Vehicle (UAV) and SfM photogrammetry survey as a function of the number and location of ground control points used[J]. Remote Sensing, 10(10): 1606. doi: 10.3390/rs10101606
    SEFERCIK U G, NAZAR M, 2023. Consistency analysis of RTK and Non-RTK UAV DSMs in vegetated areas[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 16: 5759-5768. doi: 10.1109/JSTARS.2023.3288947
    SIMIC MILAS A, CRACKNELL A P, WARNER T A, 2018. Drones-the third generation source of remote sensing data[J]. International Journal of Remote Sensing, 39(21): 7125-7137. doi: 10.1080/01431161.2018.1523832
    TURNER D, LUCIEER A, WATSON C, 2012. An automated technique for generating georectified mosaics from ultra-high resolution Unmanned Aerial Vehicle (UAV) imagery, based on Structure from Motion (SfM) point clouds[J]. Remote Sensing, 4(5): 1392-1410. doi: 10.3390/rs4051392
    THOMAS A F, AMY E F, ADAM J M, et al., 2020. Impacts of abrupt terrain changes and grass cover on vertical accuracy of UAS-SfM derived elevation models[J]. Papers in Applied Geography, 6(4): 336-51. doi: 10.1080/23754931.2020.1782254
    WANG J W, LI C L, WANG Z Y, et al., 2021. Analysis on the influence of images on measurement accuracy of three-dimensional model reconstructed by SFM[J]. Laser Journal, 42(3): 63-69. (in Chinese with English abstract)
    WANG P T, SHAO Y X, ZHANG H P, et al., 2016. The application of sUAV photogrammetry in active tectonics: Shanmagou site of Haiyuan Fault, for example[J]. Quaternary Sciences, 36(2): 433-442. (in Chinese with English abstract)
    WESTOBY M J, BRASINGTON J, GLASSER N F, et al., 2012. 'Structure-from-Motion' photogrammetry: a low-cost, effective tool for geoscience applications[J]. Geomorphology, 179: 300-314. doi: 10.1016/j.geomorph.2012.08.021
    YANG H B, YANG X P, HUANG X N, et al., 2016. Data comparative analysis between SfM data and DGPs data: a case study from fault scarp in the East Bank of Hongshuiba River, northern margin of the Qilian Shan[J]. Seismology and Geology, 38(4): 1030-1046. (in Chinese with English abstract)
    ZHANG D, LI J C, WU Z H, et al., 2021. Using terrestrial LiDAR to accurately measure the micro-geomorphologic geometry of active fault: a case study of fault scarp on the Maoyaba Fault zone[J]. Journal of Geomechanics, 27(1): 63-72. (in Chinese with English abstract)
    ZHANG H P, LIU S F, SUN Y P, et al., 2006. The acquisition of local topographic relief and its application: an SRTM-DEM analysis[J]. Remote Sensing for Land & Resources, (1): 31-35. (in Chinese with English abstract)
    ZIELKE O, ARROWSMITH J R, 2012. LaDiCaoz and LiDARimager—MATLAB GUIs for LiDAR data handling and lateral displacement measurement[J]. Geosphere, 8(1): 206-221. doi: 10.1130/GES00686.1
    毕海芸, 郑文俊, 曾江源, 等, 2017. SfM摄影测量方法在活动构造定量研究中的应用[J]. 地震地质, 39(4): 656-674. https://www.cnki.com.cn/Article/CJFDTOTAL-DZDZ201704003.htm
    曹鹏举, 程三友, 林海星, 等, 2021. DEM在构造地貌定量分析中的应用与展望[J]. 地质力学学报, 27(6): 949-962. doi: 10.12090/j.issn.1006-6616.2021.27.06.077?viewType=HTML
    陈薪伊, 史扬子, 杨扬, 等, 2023. SfM摄影测量法对黄土高原典型切沟的测量精度评价[J]. 陕西师范大学学报(自然科学版), 51(6): 25-36. https://www.cnki.com.cn/Article/CJFDTOTAL-SXSZ202306003.htm
    邓起东, 陈立春, 冉勇康, 2004. 活动构造定量研究与应用[J]. 地学前缘, 11(4): 383-392. https://www.cnki.com.cn/Article/CJFDTOTAL-DXQY200404006.htm
    郭庆华, 胡天宇, 刘瑾, 等, 2021. 轻小型无人机遥感及其行业应用进展[J]. 地理科学进展, 40(9): 1550-1569. https://www.cnki.com.cn/Article/CJFDTOTAL-DLKJ202109011.htm
    韩帅, 吴中海, 王世锋, 等, 2023. 羌塘地块中西部布木错走滑断裂系晚第四纪以来地表变形特征与构造意义[J/OL]. 地质力学学报, DOI: 10.12090/j.issn.1006-6616.2023086.
    康文君, 徐锡伟, 于贵华, 等, 2020. 2种基于Matlab平台的断层位移测量软件对比分析: 以阿尔金断裂东段为例[J]. 地震地质, 42(3): 732-747. https://www.cnki.com.cn/Article/CJFDTOTAL-DZDZ202003013.htm
    李红强, 袁道阳, 苏琦, 等, 2023. 祁连山内部门源盆地地貌特征及构造意义[J]. 地质力学学报, 29(6): 824-841. doi: 10.12090/j.issn.1006-6616.2023123?viewType=HTML
    廖程, 梁明剑, 周文英, 等, 2024. 基于无人机SfM及LaDiCaoz的地震地表破裂定量参数提取: 以炉霍扎交村一带地震典型地表破裂为例[J]. 大地测量与地球动力学, 44(2): 183-188. https://www.cnki.com.cn/Article/CJFDTOTAL-DKXB202402014.htm
    马晓雪, 吴中海, 李家存, 2016. LiDAR技术在地质环境中的主要应用与展望[J]. 地质力学学报, 22(1): 93-103. https://journal.geomech.ac.cn/article/id/0f502c82-0ca8-4348-9b7a-ba4406be4e74?viewType=HTML
    任治坤, 陈涛, 张会平, 等, 2014. LiDAR技术在活动构造研究中的应用[J]. 地质学报, 88(6): 1196-1207. https://www.cnki.com.cn/Article/CJFDTOTAL-DZXE201406019.htm
    王佳文, 李彩林, 王志勇, 等, 2021. 影像数量对SFM三维重建模型测量精度的影响分析[J]. 激光杂志, 42(3): 63-69. https://www.cnki.com.cn/Article/CJFDTOTAL-JGZZ202103012.htm
    王朋涛, 邵延秀, 张会平, 等, 2016. sUAV摄影技术在活动构造研究中的应用: 以海原断裂骟马沟为例[J]. 第四纪研究, 36(2): 433-442. https://www.cnki.com.cn/Article/CJFDTOTAL-DSJJ201602018.htm
    杨海波, 杨晓平, 黄雄南, 等, 2016. 移动摄影测量数据与差分GPS数据的对比分析: 以祁连山北麓洪水坝河东岸断层陡坎为例[J]. 地震地质, 38(4): 1030-1046. https://www.cnki.com.cn/Article/CJFDTOTAL-DZDZ201604018.htm
    张迪, 李家存, 吴中海, 等, 2021. 利用地面LiDAR精细化测量活断层微地貌形态: 以毛垭坝断裂禾尼处断层崖为例[J]. 地质力学学报, 27(1): 63-72. doi: 10.12090/j.issn.1006-6616.2021.27.01.007?viewType=HTML
    张会平, 刘少峰, 孙亚平, 等, 2006. 基于SRTM-DEM区域地形起伏的获取及应用[J]. 国土资源遥感, (1): 31-35. https://www.cnki.com.cn/Article/CJFDTOTAL-GTYG200601006.htm
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